To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("groHMM")
In most cases, you don't need to download the package archive at all.
groHMM
GRO-seq Analysis Pipeline.
Bioconductor version: 3.0
A pipeline for the analysis of GRO-seq data.
Author: Charles G. Danko, Minho Chae, Andre Martins, W. Lee Kraus
Maintainer: Minho Chae<minho.chae at gmail.com>, W. Lee Kraus <lee.kraus at utsouthwestern.edu>
Citation (from within R,
enter citation("groHMM")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("groHMM")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("groHMM")
| R Script | groHMM tutorial | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Sequencing, Software |
| Version | 1.0.2 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 3.0.2), MASS, S4Vectors, IRanges, GenomicRanges, GenomicAlignments, rtracklayer, parallel |
| Imports | |
| LinkingTo | |
| Suggests | BiocStyle, GenomicFeatures, edgeR, org.Hs.eg.db, TxDb.Hsapiens.UCSC.hg19.knownGene |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | groHMM_1.0.2.tar.gz |
| Windows Binary | groHMM_1.0.2.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | groHMM_1.0.2.tgz |
| Mac OS X 10.9 (Mavericks) | groHMM_1.0.2.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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